Being in Control of Noise Levels Improves the Perception of Airplane Seat Comfort

The aviation industry is constantly making compromises when designing comfortable airplane cabins. Providing passengers with a pleasant acoustic environment without adding weight to the cabin structure is a field of tension that challenges cabin interior designers. The aim of this study was to investigate whether noise levels affect the comfort and physical discomfort experienced by airplane passengers, and whether control influences comfort perception. To this end, 30 participants experienced three conditions (silence, aircraft engine noise at 75 dB, and the same noise with the ability to use earplugs), and comfort and discomfort were measured using a questionnaire. It was concluded that aircraft engine noise negatively affected the airplane passengers’ comfort experiences. Having the ability to control this noisy environment with earplugs resulted in the lowest reported physical discomfort.

Architectural Interior Modeling Product Design Based on the Multimedia Three-Dimensional Hybrid Algorithm

With the continuous development of social economy, people’s aspiration for architecture is getting higher and higher. Designing more functional and aesthetically pleasing interior styling products is increasingly important research. Relying on the multimedia three-dimensional hybrid algorithm, the mathematical modeling of the relationship between visual comfort and chromaticity is modeled in this paper, to construct an economical and practical interior architectural design model that takes into account color comfort perception, that is, complete “design, conversion, editing and repair, and semantic and coordinate supplement” and other chain construction to realize usable interior architectural design models. The simulation experiment results show that the model based on the multimedia 3D hybrid algorithm has high practicability.

Environmental thermal influence over soundscape perception: a test room experimental campaign involving the psychological and physiological description of the indoor environment

Human environmental perception leads occupants’ behaviour when interacting with buildings components, affecting the final building energy performance. A solid understanding of human comfort perception includes simultaneous multisensory stimuli and cross-modal interactions among different comfort domains. This study aims to explore the cross-modal effect between thermal and acoustic domains. Each of the 40 subjects took part in a multisensory survey under two different stationary environmental temperature settings. Results show that people in thermally warm conditions are less confident in describing the provided acoustic records. To perform the same procedure but providing a decreasing air temperature ramp would lead to a better interpretation of the results of this campaign.

Reshaping energy policy based on social and human dimensions: an analysis of human-building interactions among societies in transition in GCC countries

Without major structural changes, social sciences can potentially bolster economic diversification and strategic planning efforts in developing countries. This article presents an analysis of a set of human-oriented dimensions to enhance energy policies associated with the building sector in developing countries with similarities to the Gulf Cooperation Council union (GCC). A clear understanding of human dimensions in the GCC union’s energy policy is crucial due to social complexities and large numbers of expatriate communities and migrant workers with unknown cultural, behavioral, and financial diversities with respect to local communities. This study evaluates the correlations of demographic, socioeconomic, and behavioral dimensions with human–building interactions to identify the main contributors that create discrepancies in human habits, well-being, motivations, responsibilities, and energy use based on a sample of 2200 respondents in Qatar. Moreover, this study is extended to explore human indoor comfort perception dependencies with building features. Behavioral associations with financial drivers, including energy subsidies and demand response programs, are investigated. The patterns in the data are analyzed and attributed to applications in energy policy concerning awareness, social well-being, and interventions. The sample is clustered into various consumer classes, and a feature importance analysis is conducted via machine learning methods to find the key contributors to consumer behavior. The outcomes show profound insight into how human factors influence consumption, consequence awareness, self-responsibility, habits, norms, and comfort perception in residential and work environments. The findings of this study can assist decision-makers in creating targeted strategies to enhance the efficacy of energy policies and improve sustainability performance indicators.

Effects of 24 h Compression Interventions with Different Garments on Recovery Markers during Running

Compression and temperature manipulation are discussed as strategies to improve performance markers and recovery in sports. Here, we investigate the effects of compression stockings made with fabric, either combined or not with heating and cooling substances, on variables related to running performance and recovery. Ten trained runners (mean ± standard deviation age 45 ± 9 years old, body mass 69 ± 7 kg, height 166 ± 4 cm) with no experience of using compression garments performed an intense running session of 10 km, then wore a stocking for 24 h (randomized; without compression, compression, compression with camphor, and compression with menthol), and were evaluated on the following day, after running 5 km. The different types of compression stockings used 24 h before exercise did not affect running kinematics (p > 0.14), skin temperature (p > 0.05), heart rate (p > 0.12; mean value of maximal heart rate 156 bpm), comfort perception (p = 0.13; mean value of 7/10 points), or perception of recovery (p = 0.13; mean value of 7/10 points). In general, there were no effects of 24 h pre-exercise lower leg compression, including those treated with menthol and camphor applications on running kinematics, skin temperature, heart rate, or recovery perception in athletes undertaking consecutive running exercises.

The Effect of Backplate Design for Mountain Bike Backpacks on Thermoregulation Mechanisms

Using infrared thermography, we assess how a new backpack design for mountain bikers can contribute to their thermoregulation process and perceived comfort during a cycling activity in a controlled environment. We gathered qualitative and quantitative data of heat concentration areas on skin temperature and thermal comfort perception by comparing two types of backpacks: a conventional backpack and a novel backpack design. Our results show that a guaranteeing airflow due to distance between the user’s back and the backpack with a rigid backplate and an arc radius morphology improves heat dissipation and thermal comfort for mountain bikers.

Modelo de Predição de Conforto de Usuários do Transporte Coletivo

The small and medium-size cities are facing problems related to mobilitythat could be avoided by adopting the public transportationsystem, as buses and trains. However, in many Brazilian cities theuse of public transportation is neglected because it is considereduncomfortable, expensive and insecure. To attract passengers forsuch kind of transportation there are several possible approaches,the promotion of comfort perception is one of those. Several studieshave already approached this problem, however, few of themaddressed the perception of comfort felt by the passengers usingtelemetry data collected from the vehicle. Among the works thatuse such data, none of them applied data mining techniques toabstract a general model of comfort perception. Therefore, thiswork aims to apply mining techniques over telemetry data collectedfrom vehicles to build a comprehensible model to classifythe level of comfort of public transportation passengers. To achievethis objective machine learning techniques were used, centered ondecision trees. Due to the complexity of abstracting the model therewere constructed three models, one for each acceleration axis thatwere merged using a meta-classifier responsible to point out thepassenger general comfort. The results have reached an accuracyof 85,2%, which can be considered a promising result regardingthe difficulties of separating the data source in sets that can betteridentify the bus drivers behaviour.